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Record W3125787938 · doi:10.1097/ipc.0000000000000992

Diabetes and Risk of COVID-19 Mortality

2021· article· en· W3125787938 on OpenAlexaboutno aff
Hend Kandil, Ahmed Ibrahim, Naglaa Afifi, Ahmed Arafa

Bibliographic record

VenueInfectious Diseases in Clinical Practice · 2021
Typearticle
Languageen
FieldMedicine
TopicCOVID-19 Clinical Research Studies
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineDiabetes mellitusCoronavirus disease 2019 (COVID-19)Case fatality rateMEDLINEDiseaseType 2 diabetesGlycemicInternal medicineIntensive care medicineEpidemiologyInfectious disease (medical specialty)Endocrinology

Abstract

fetched live from OpenAlex

To the Editor A growing body of evidence has suggested that patients with diabetes who developed the novel corona virus disease (COVID-19) might have shown increased mortality. Biologically, patients with diabetes have glycemic instability, impaired immune response, and associated comorbidities such as obesity and heart diseases, factors that could explain the high COVID-19 mortalities among patients with diabetes.1 Epidemiologically, numerous studies assessed the possible relationship between diabetes and COVID-19 mortalities, but most of them were limited by the small sample size in addition to reaching inconsistent findings.2–16 We, therefore, combined the results of the published studies via a meta-analysis to precisely detect the excess risk of COVID-19 mortality attributed to diabetes. First, we searched MEDLINE (PubMed), Web of Science, and Scopus for potential studies published before May 31, 2020, using relevant search terms (diabetes OR diabetes mellitus OR type 2 diabetes OR DM) AND (COVID-19 OR SARS-COV 2 OR coronavirus) AND (outcomes OR mortality OR fatality OR deaths). The study was considered eligible if 1) it was published in English, 2) the exposure was COVID-19 patients with diabetes in comparison with COVID-19 patients without diabetes, 3) the outcome was COVID-19 mortality, and 4) the number of COVID-19 patients with diabetes is 50 or more. After reviewing the abstracts of all studies detected by the primary search, we reached a shortlist of studies from which the following relevant information was extracted: last name of the first author, country, sample size, method of diabetes diagnosis, odds ratios (ORs) with corresponding 95% confidence intervals (CIs), and the quality of studies as determined using the modified Newcastle-Ottawa Scale (NOS) (Table 1). The fixed- or random-effects model was used to compute the pooled ORs. The I2 was calculated to test the statistical heterogeneity across studies. A forest plot showing the ORs with their 95% CIs and study weights of the selected studies in addition to the pooled OR (95% CI) and I2 was presented (Fig. 1). Sensitivity analysis was conducted to assess the influence of individual studies on the pooled OR and I2 by leaving out one study and combining the remaining studies in separate analyses. Publication bias was assessed using the regression test for funnel plot asymmetry. R-3.2.0 statistical package (Metafor: A Meta-Analysis Package for R) was used for analysis. TABLE 1 - Characteristics of the Included Studies Study Country Overall Patients Diabetes Patients Diabetes Diagnosis Quality by Modified NOS Zhu L China 7337 952 Records based on the Chinese guidelines for type 2 diabetes prevention and control 8 Chen Y China 904 136 Records based on the World Health Organization diagnostic criteria 7 Shi Q China 306 153 Records based on the American Diabetes Association guidelines 7 Guan W China 1590 130 Self-report 6 Wang L China 339 54 Records 7 Nikpouraghdam M Iran 2968 113 Records 5 Bode B USA 1122 194 HbA1c ≥6.5% 7 Li H China 453 192 FG ≥7 mmol/L and/or HbA1c ≥6.5% 7 Bello-Chavolla O Mexico 51,633 9460 Medical history 7 Richardson S USA 5700 1808 Records 7 Zhang Y China 166 61 Self-report, high FG, and/or HbA1c ≥6.5% 8 Wang Y China 344 64 Records 5 Chen R China 1590 130 Records 7 Wang K China 548 83 Records 5 Palaiodimos L USA 200 79 Records 7 FG indicates fasting glucose. FIGURE 1: Meta-analysis of the included studies.Eventually, we retrieved a total of 831 studies before excluding 431 duplicates; 327 articles for being written in a non-English language, case reports, comments, reviews, or unrelated; 41 articles for not examining COVID-19 mortality or not including a comparison group; and 21 articles for including less than 50 COVID-19 patients with diabetes, leaving a shortlist of 15 studies for this meta-analysis. Most of the included studies were conducted in China, whereas only 5 studies were conducted out of China (3 studies in the United States and 1 study in each of Iran and Mexico). The studies included 75,200 COVID-19 patients, of which 13,609 had concomitant diabetes. According to the modified NOS, most studies were of average to good quality (Table 1). A total of 8 studies showed statistically significant associations between diabetes and COVID-19 mortality, whereas 7 studies indicated no significant association. Combining the ORs of all studies revealed that COVID-19 patients with diabetes had an 87% higher risk of death than COVID-19 patients without diabetes (pooled OR, 1.87; 95% CI, 1.51–2.31). However, we could notice a high degree of heterogeneity across studies (I2 = 77.9%; P value for heterogeneity <0.001) (Fig. 1). This heterogeneity could be partially explained by the wide variation in the sample size among studies and the differences in the sociodemographic characteristics between study populations. Leaving out studies one by one and combining the remainders in separate analyses did not significantly affect the pooled risk or the heterogeneity across studies. No signs of publication bias could be detected (Z = 1.078; P value for publication bias = 0.281). Our results came in line with similar meta-analyses that put the risk of COVID-19 mortality among patients with diabetes compared with COVID-19 patients without diabetes between 1.75 and 2.68 and showed moderate to high degrees of heterogeneity between their studies.17–20 In conclusion, our results confirmed the previous findings indicating that COVID-19 patients with diabetes were highly vulnerable to a lethal outcome. Hend Kandil, MD Faculty of Medicine, Menoufia University Menoufia, EgyptAhmed Elsayed Ibrahim, MD Faculty of Medicine, Alexandria University Alexandria, EgyptNaglaa Afifi, MD, PhD Department of Internal Medicine, Faculty of Medicine Ain Shams University Cairo, Egypt Department of Internal Medicine Armed Forces College of Medicine (AFCM) Cairo, EgyptAhmed Arafa, MD, MSc Department of Public Health Graduate School of Medicine, Osaka University Osaka, Japan [email protected] Department of Public Health, Faculty of Medicine Beni-Suef University Beni-Suef, Egypt

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How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.005
metaresearch head score (Gemma)0.864
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.859
Threshold uncertainty score0.633

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0050.864
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.092
GPT teacher head0.538
Teacher spread0.446 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

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Citations7
Published2021
Admission routes1
Has abstractyes

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